ArticleNature biotechnology2024
Direct measurement of engineered cancer mutations and their transcriptional phenotypes in single cells.
Article in Nature biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 23 citations in OpenAlex.
- Analysing long-read CRISPR experiments with CRISPRLungo.Nature biomedical engineering · 2026Article
- Alpelisib enhances cisplatin mediated cytotoxicity in non-mutated, PIK3CA-dependent high-grade serous ovarian cancer.Journal of ovarian research · 2026Article
- Multiplexed single-cell transcriptomics reveals diverse phenotypic outcomes for pathogenic SHP2 variants.Science advances · 2026Article
- Nucleotide-resolution mapping of regulatory elements via allelic readout of tiled base editing.Nature communications · 2026Article
- Bridging the variant-to-function gap in type 2 diabetes: advances and challenges.Diabetologia · 2026Review
- The Multifaceted Role of p53 in Cancer Molecular Biology: Insights for Precision Diagnosis and Therapeutic Breakthroughs.Biomolecules · 2025Review
- CLONEID: A Framework for Longitudinal Integration of Phenotypic and Genotypic Data to Monitor and Steer Subclonal Dynamics.bioRxiv : the preprint server for biology · 2025Article
- Reply to 'Heterogeneity of TP53 mutations necessitates differentiation with p53-rescue therapies'.Nature reviews. Cancer · 2025Article
- Large-scale discovery of chromatin dysregulation induced by oncofusions and other protein-coding variants.Nature biotechnology · 2025Article
- Rapid and robust validation of pooled CRISPR knockout screens using CelFi.Scientific reports · 2025Article
- Single-cell splicing QTL analysis in pancreatic islets.Frontiers in bioinformatics · 2025Article
- Rapid mechanical phenotyping of breast cancer cells based on stochastic intracellular fluctuations.iScience · 2024Article
- Review
- Discovering mechanisms of human genetic variation and controlling cell states at scale.Trends in genetics : TIG · 2024Review
- Analyzing the functional effects of DNA variants with gene editing.Cell reports methods · 2024Review
- Deconstructing cancer with precision genome editing.Biochemical Society transactions · 2024Review
- scSNV-seq: high-throughput phenotyping of single nucleotide variants by coupled single-cell genotyping and transcriptomics.Genome biology · 2024Article
- Translation of genome-wide association study: from genomic signals to biological insights.Frontiers in genetics · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 5 institutions in 2 countries.
Funding
Abstract
Genome sequencing studies have identified numerous cancer mutations across a wide spectrum of tumor types, but determining the phenotypic consequence of these mutations remains a challenge. Here, we developed a high-throughput, multiplexed single-cell technology called TISCC-seq to engineer predesignated mutations in cells using CRISPR base editors, directly delineate their genotype among individual cells and determine each mutation's transcriptional phenotype. Long-read sequencing of the target gene's transcript identifies the engineered mutations, and the transcriptome profile from the same set of cells is simultaneously analyzed by short-read sequencing. Through integration, we determine the mutations' genotype and expression phenotype at single-cell resolution. Using cell lines, we engineer and evaluate the impact of >100 TP53 mutations on gene expression. Based on the single-cell gene expression, we classify the mutations as having a functionally significant phenotype.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.